A virtual power plant carbon emission reduction contribution allocation method and device

Abstract

The application discloses a virtual power plant carbon emission reduction contribution distribution method and device, and based on the carbon emission reduction contribution initial value calculated by the two sets of carbon emission flow distribution before and after response, the physical value misjudgment generated by only distributing according to the proportion of response power or power can be avoided, on the basis, the response time, response deviation and carbon potential sensitivity are further introduced to calculate the correction coefficient, so that the initial contribution value is corrected, the response behavior with fast response speed, high execution accuracy and acting on the high carbon potential area can obtain higher contribution evaluation, so that the response quality difference is organically integrated into the contribution measurement process, the measurement of the virtual power plant carbon emission reduction contribution has a clear power grid physical basis, the distribution result can truly reflect the marginal emission reduction value of each resource, thereby the reliability and accuracy of the virtual power plant carbon emission reduction contribution distribution are significantly improved.

Description

Technical Field

[0001] This invention relates to the field of carbon emission contribution allocation technology, and in particular to a method and apparatus for allocating carbon emission reduction contributions from a virtual power plant. Background Technology

[0002] Currently, with the deepening of the construction of new power systems and the large-scale development of virtual power plant technology, various types of resources, such as distributed photovoltaics, energy storage systems, controllable loads, and charging facilities, are gradually being integrated into the power grid dispatching system. Virtual power plants, by aggregating dispersed distributed resources, can play a crucial role in peak shaving and valley filling, load regulation, renewable energy consumption, and ancillary services. Accurately measuring the actual impact of each virtual power plant response on grid carbon emissions and fairly and reasonably allocating emission reduction contributions to the various distributed resources within the plant is a vital foundation for enabling virtual power plants to participate in carbon market trading and for the effective operation of demand response incentive mechanisms.

[0003] Existing methods for assessing the response contribution of virtual power plants primarily rely on response power, response volume, or dispatch command completion rate, allocating contributions according to the output or volume ratio of each resource. However, due to the varying power source structures at different nodes and time periods within the power grid, the carbon emission intensity implied per unit of electricity differs significantly. Allocating contributions solely based on volume ratio can lead to misjudgments in scenarios where "the same output carries different carbon emissions." Furthermore, different resources exhibit significant differences in response speed, sustainability, execution deviation, and node carbon potential; allocating based solely on actual regulation volume fails to reflect the differences in response quality and marginal emission reduction effects. Summary of the Invention

[0004] This invention provides a method and apparatus for allocating carbon emission reduction contributions from virtual power plants, thereby improving the reliability and accuracy of carbon emission reduction contribution allocation from virtual power plants.

[0005] To address the aforementioned technical problems, this invention provides a method for allocating carbon emission reduction contributions from a virtual power plant, comprising: Obtain the first operating data before the virtual power plant responds, and calculate the first node carbon potential and first load carbon flow rate of each node based on the first operating data to generate the first carbon emission flow distribution; Obtain the second operating data after the virtual power plant responds, and calculate the second carbon emission flow distribution based on the second operating data; The difference in total load carbon flow rate is calculated based on the first carbon emission flow distribution and the second carbon emission flow distribution, and the initial value of carbon emission reduction contribution is calculated based on the difference in total load carbon flow rate. The response time, response deviation, and carbon potential sensitivity of the virtual power plant are statistically analyzed. Based on the response time, response deviation, and carbon potential sensitivity, a correction coefficient is calculated, and the initial value of the carbon emission reduction contribution is corrected based on the correction coefficient to obtain the effective carbon emission reduction contribution. Based on the adjustment amount of each distributed resource, the carbon potential of the first node of the node, and the response quality of each distributed resource, the effective carbon emission reduction contribution is allocated to each distributed resource to obtain the carbon emission reduction contribution corresponding to each distributed resource.

[0006] This invention calculates the carbon emission flow distribution before and after a virtual power plant's response by acquiring operational data before and after the response. This allows each response behavior of the virtual power plant to be measured within the actual carbon flow physical field of the power grid. Since the carbon emission flow distribution reflects the true spatial distribution of carbon potential and load carbon flow rate at each node, the initial carbon reduction contribution calculated based on the two sets of carbon emission flow distributions before and after the response avoids misjudgments of physical value caused by allocating solely based on the response electricity or power ratio. Furthermore, this invention introduces correction coefficients for response time, response deviation, and carbon potential sensitivity to correct the initial contribution value. This results in responses with fast response speeds, high execution accuracy, and those operating in high carbon potential regions receiving higher contribution evaluations, thus organically integrating response quality differences into the contribution measurement process. Meanwhile, this invention considers the adjustment amount of each distributed resource, the carbon potential level of the node, and the individual response quality in the allocation process. This ensures that the differences in adjustment capabilities, spatial location, and performance of different types of resources are fairly reflected in the final allocation results. This gives the measurement of carbon emission reduction contribution of virtual power plants a clear physical basis for the power grid, and the allocation results can truly reflect the marginal emission reduction value of each resource, thereby significantly improving the reliability and accuracy of the allocation of carbon emission reduction contribution of virtual power plants.

[0007] Furthermore, the step of acquiring the first operating data before the virtual power plant responds, and calculating the first node carbon potential and first load carbon flow rate of each node based on the first operating data to generate the first carbon emission flow distribution, includes: The first operating data of the power grid before the response is obtained, including the topology, the active power flow of the first branch, the first active power output of each generator set, the carbon emission intensity of each generator set, and the first load power of each node. Based on the first active power output of each generator set and its corresponding carbon emission intensity, calculate the first carbon flow rate injected into the grid by each generator set. Based on the aforementioned topology, the first carbon flow rate injected into the power grid by each generator set, and the active power flow of the first branch, the first node carbon potential of each node is calculated. Calculate the first load carbon flow rate of each node based on the first load power and the first node carbon potential. The first carbon emission flow distribution is generated based on the first node carbon potential and the first load carbon flow rate of all nodes.

[0008] This invention acquires the grid topology, active power flow of the first branch, the first active power output of each generator unit and its corresponding carbon emission intensity, and the first load power of each node before the response. Based on the correspondence between the output of each generator unit and its carbon emission intensity, it calculates the first carbon flow rate injected into the grid by each generator unit, thereby mapping the carbon emission attributes of the generation side to the grid power injection end in the form of carbon flow rate. On this basis, it calculates the first node carbon potential of each node using the topology, the first carbon flow rate injected by each generator unit, and the active power flow of the first branch. This ensures that the carbon potential of each node is determined based on both upstream carbon flow injection and local generation carbon flow injection, avoiding the spatial difference neglect problem caused by using a uniform carbon emission factor. Furthermore, it calculates the first load carbon flow rate of each node based on the first load power and the first node carbon potential, thereby transforming the node carbon potential into the actual carbon emission responsibility on the load side, providing a node-level fine-grained ground-state data foundation for subsequent comparison of carbon emission flows before and after the response.

[0009] Furthermore, the calculation of the first-node carbon potential of each node based on the topology, the carbon flow rate injected into the grid by each generator set, and the active power flow of the branches includes: The carbon flow rate injected into the power grid by each generator set is used as the initial carbon flow source. Along the flow direction of the active power flow of the branch, the carbon flow rate is transmitted to each branch and node of the power grid in a step-by-step manner according to the preset power distribution ratio. For each node, the first node carbon potential is calculated based on the sum of all carbon flow rates flowing into the node and the total active power flowing into the node.

[0010] This invention uses the carbon flow rate injected into the power grid by each generator unit as the initial carbon flow source. Along the active power flow direction of the branches, the carbon flow rate is progressively transferred to each branch and node of the power grid according to the power distribution ratio. This ensures that the carbon flow carried by each active power in the power grid is distributed according to its actual flow path, rather than using a statistical average to allocate carbon responsibility. Based on this, for each node, the node carbon potential is calculated based on all carbon flow rates flowing into that node and the total active power flowing into that node. This ensures that the carbon potential per unit of electricity at that node accurately reflects the weighted average result of the carbon flow flowing into that node. This progressive transfer method based on power ratio allocation fully preserves the dynamic migration characteristics of carbon flow with power flow distribution, enabling the node carbon potential to respond sensitively to changes in the power grid operation mode. It provides an accurate and physically consistent node carbon potential input for subsequent calculations of the carbon flow difference before and after the response.

[0011] Furthermore, the step of obtaining the second operating data after the virtual power plant's response, and calculating the second carbon emission flow distribution based on the second operating data, includes: After obtaining the response, the second operating data of the power grid includes the topology, the active power flow of the second branch, the second active power output of each generator set, the carbon emission intensity of each generator set, and the second load power of each node. Based on the second active power output of each generator set and its corresponding carbon emission intensity, the second carbon flow rate injected into the grid by each generator set is calculated. Based on the aforementioned topology, the second carbon flow rate injected into the grid by each generator set, and the active power flow of the second branch, the second node carbon potential of each node is calculated. Calculate the second load carbon flow rate of each node based on the second load power and the second node carbon potential. The second carbon emission flow distribution is generated based on the second node carbon potential and the second load carbon flow rate of all nodes.

[0012] This invention, after the virtual power plant completes its response, obtains the post-response grid topology, active power flow of the second branch, the second active power output of each generator unit and its corresponding carbon emission intensity, and the second load power of each node. It then calculates the second carbon flow rate injected by each generator unit, the second node carbon potential of each node, and the second load carbon flow rate of each node, thereby generating the second carbon emission flow distribution. Because a unified carbon flow tracking method and the same calculation rules are used before and after the response, the difference between the two calculation results stems only from the changes in grid operating status caused by the virtual power plant's response behavior, resulting in good attribution consistency in the comparison of carbon flow distribution before and after the response. Simultaneously, the post-response power flow data naturally contains the impact of the virtual power plant's response behavior on the global distribution of grid carbon flow, providing a complete physical causal chain for subsequent emission reduction contribution calculations.

[0013] Furthermore, the step of calculating the difference in total load carbon flow rate based on the first carbon emission flow distribution and the second carbon emission flow distribution, and calculating the initial value of carbon emission reduction contribution based on the difference in total load carbon flow rate, includes: The first load carbon flow rate of each node is obtained based on the first carbon emission flow distribution, and the pre-response load carbon flow rate is obtained by summing the first load carbon flow rates of all nodes. The second load carbon flow rate of each node is obtained based on the second carbon emission flow distribution, and the load carbon flow rate after response is obtained by summing the second load carbon flow rates of all nodes. Calculate the load carbon flow rate difference between the pre-response load carbon flow rate and the post-response load carbon flow rate; The initial value of the carbon emission reduction contribution is calculated based on the response time of the virtual power plant and the difference in load carbon flow rate.

[0014] This invention obtains the total system load carbon flow rate before the response by summing the first load carbon flow rates of all nodes, and obtains the total system load carbon flow rate after the response by summing the second load carbon flow rates of all nodes. Subtracting the two yields the load carbon flow rate difference, which directly measures the net change in the total carbon emission responsibility of the grid load side caused by the virtual power plant's response behavior. Based on this, the difference is accumulated over time along the response duration to obtain an initial value of the total carbon emission reduction brought to the grid by the virtual power plant throughout the entire response event. Since a decrease in the total system load carbon flow rate signifies a real decrease in the overall carbon emission pressure of the grid, this method of calculating the initial contribution based on changes in global load carbon flow rate provides a macroscopic verification basis for the emission reduction contribution of the virtual power plant, using changes in the carbon flow rate of the entire grid as a benchmark.

[0015] Furthermore, the response time, response deviation, and carbon potential sensitivity of the statistical virtual power plant are used to calculate a correction coefficient. This correction coefficient is then used to adjust the initial value of the carbon emission reduction contribution to obtain the effective carbon emission reduction contribution, including: The response time of the virtual power plant is statistically analyzed, and a response time correction parameter is calculated based on the response time. Obtain the dispatch command power curve and the actual response power curve of the virtual power plant, calculate the response deviation based on the dispatch command power curve and the actual response power curve, and calculate the response reliability correction coefficient based on the response deviation; The nodal carbon potential change at the grid connection point of the virtual power plant is statistically analyzed. Based on the nodal carbon potential change and the total response power, the carbon potential sensitivity is calculated. Based on the ratio of the carbon potential sensitivity to the maximum carbon potential sensitivity in the preset area, the carbon potential sensitivity correction coefficient is calculated. The initial value of the carbon emission reduction contribution is corrected based on the response time correction coefficient, response reliability correction coefficient, and carbon potential sensitivity correction coefficient to obtain the effective carbon emission reduction contribution.

[0016] This invention constructs correction parameters from three dimensions: response time, response deviation, and carbon potential sensitivity. First, a response time correction parameter is calculated based on response time to evaluate the timeliness of the virtual power plant's response to dispatch instructions. Next, a response reliability correction coefficient is calculated based on the deviation between the dispatch instruction power curve and the actual response power curve to evaluate the execution accuracy of the virtual power plant. Finally, carbon potential sensitivity is calculated based on the change in carbon potential at the grid connection point combined with the total response power, and a carbon potential sensitivity correction coefficient is calculated based on the ratio of the carbon potential sensitivity to the maximum carbon potential sensitivity in the preset area to evaluate the actual impact of the response behavior on the grid's carbon potential. These three correction parameters respectively cover the efficiency characteristics, accuracy characteristics, and carbon emission reduction effect characteristics of the virtual power plant's response. After applying the three correction coefficients together to the initial contribution value, response behaviors with fast response speed, small execution deviation, and high carbon potential sensitivity can obtain a higher effective contribution, while response behaviors with lag, large deviation, or low carbon potential sensitivity are reasonably reduced, ensuring that the final effective contribution truly reflects the comprehensive value of the virtual power plant's response behavior.

[0017] Furthermore, the step of correcting the initial value of the carbon emission reduction contribution based on the response time correction coefficient, response reliability correction coefficient, and carbon potential sensitivity correction coefficient to obtain the effective carbon emission reduction contribution includes: The response time correction coefficient, response reliability correction coefficient, and carbon potential sensitivity correction coefficient are weighted and summed based on preset weights to obtain a comprehensive correction coefficient. The effective carbon emission reduction contribution is determined by multiplying the initial value of the carbon emission reduction contribution with the comprehensive correction coefficient.

[0018] This invention obtains a comprehensive correction coefficient by weighting and summing the response time correction coefficient, response reliability correction coefficient, and carbon potential sensitivity correction coefficient with preset weights. The weighting configuration allows for flexible adjustment of the influence of each dimension in the comprehensive evaluation, adapting to the evaluation emphasis requirements of different application scenarios. Based on this, the initial value of carbon emission reduction contribution is multiplied by the comprehensive correction coefficient to determine the effective carbon emission reduction contribution. This ensures that the final effective contribution of each response event is positively correlated with its overall response quality, providing a reasonable allocation base for subsequent internal resource contribution allocation after quality screening and value correction.

[0019] Furthermore, the response time includes the response command issuance time, the actual response start time, the scheduling request response duration, and the actual continuous response duration; the step of statistically analyzing the response time of the virtual power plant and calculating response time correction parameters based on the response time includes: Calculate the time difference between the time the response instruction is issued and the actual response start time. Based on the time difference and the proportion of the scheduling requirement response time, calculate the response speed correction value. Calculate the response duration correction value based on the ratio of the actual continuous response duration to the scheduled response duration. The response time correction parameter is obtained by weighted summing of the response speed correction value and the response duration correction value.

[0020] This invention calculates a response speed correction value based on the ratio of the time difference between the response command issuance time and the actual response start time to the required response time, which directly reflects the agility of the virtual power plant in responding to dispatch commands. It also calculates a response duration correction value based on the ratio of the actual continuous response time to the required response time, which reflects the virtual power plant's response sustaining capability. By weighted summing these two correction values ​​to obtain a response time correction parameter, the invention effectively evaluates both response agility and response duration, distinguishing between two different response qualities: rapid response with mid-process withdrawal and stable, continuous response completion.

[0021] Furthermore, the allocation of the effective carbon reduction contribution to each distributed resource based on the adjustment amount of each distributed resource, the carbon potential of the first node of the node where it is located, and the response quality of each distributed resource, to obtain the carbon reduction contribution corresponding to each distributed resource, includes: Based on the resource type, adjustment direction, and adjustment amount of each distributed resource, determine the effective emission reduction adjustment amount of each distributed resource; Based on the effective emission reduction adjustment amount of each distributed resource, the carbon potential of the first node of the node where it is located, and the response time, the basic contribution value of each distributed resource is calculated, and the basic contribution values ​​of all distributed resources are summed to obtain the total basic contribution value. Based on the individual response time, individual execution deviation, and node carbon potential level of each distributed resource, the basic contribution value and the total basic contribution value of each distributed resource are corrected to obtain the corrected contribution value and the total corrected contribution value of each distributed resource. The allocation weight of each distributed resource is determined based on the ratio between the correction contribution value of each distributed resource and the total correction contribution value of the distributed resources. The effective carbon emission reduction contribution is allocated based on the allocation weight to obtain the carbon emission reduction contribution corresponding to each distributed resource.

[0022] This invention first determines the effective emission reduction adjustment amount of each distributed resource based on its resource type, adjustment direction, and adjustment amount. Then, it calculates the basic contribution value of each resource by multiplying the effective emission reduction adjustment amount, the carbon potential of the node, and the response time, and sums these to obtain the total basic contribution value. This ensures that resources with large adjustment amounts and located in high-carbon-potential nodes receive higher basic contributions. Furthermore, it introduces the individual response time, individual execution deviation, and node carbon potential level of each resource to correct the basic contribution value and the total basic contribution value, obtaining corrected contribution values ​​and a corrected total contribution value for each resource. This allows resources with timely responses, accurate execution, and located in high-carbon-potential regions to receive additional gains in allocation. Finally, it determines the allocation weight based on the proportion of each resource's corrected contribution value in the total corrected contribution value, and allocates the effective carbon emission reduction contribution accordingly. This ensures that the final contribution amount allocated to each resource reflects both its actual physical adjustment contribution and its differences in response quality and marginal emission reduction value, avoiding the incentive bias caused by allocation solely based on electricity or power.

[0023] In a second aspect, the present invention provides a virtual power plant carbon emission reduction contribution allocation device, comprising: a first carbon emission flow distribution calculation module, a second carbon emission flow distribution calculation module, a carbon emission reduction contribution initial value calculation module, a correction module, and an allocation module; The first carbon emission flow distribution calculation module is used to acquire the first operating data before the virtual power plant responds, and calculate the first node carbon potential and the first load carbon flow rate of each node based on the first operating data to generate the first carbon emission flow distribution; The second carbon emission flow distribution calculation module is used to obtain the second operating data after the virtual power plant responds, and calculate the second carbon emission flow distribution based on the second operating data; The carbon emission reduction contribution initial value calculation module is used to calculate the difference in total load carbon flow rate based on the first carbon emission flow distribution and the second carbon emission flow distribution, and to calculate the initial value of carbon emission reduction contribution based on the difference in total load carbon flow rate. The correction module is used to statistically analyze the response time, response deviation, and carbon potential sensitivity of the virtual power plant, calculate the correction coefficient based on the response time, response deviation, and carbon potential sensitivity, and correct the initial value of the carbon emission reduction contribution based on the correction coefficient to obtain the effective carbon emission reduction contribution. The allocation module is used to allocate the effective carbon emission reduction contribution to each distributed resource based on the adjustment amount of each distributed resource, the carbon potential of the first node of the node where it is located, and the response quality of each distributed resource, so as to obtain the carbon emission reduction contribution corresponding to each distributed resource. Attached Figure Description

[0024] Figure 1 A schematic flowchart of a method for allocating carbon emission reduction contributions from a virtual power plant, provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of a virtual power plant carbon emission reduction contribution allocation device provided in an embodiment of the present invention. Detailed Implementation

[0025] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0026] The terms "first" and "second," etc., in the specification, claims, and drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such processes, methods, products, or apparatus.

[0027] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0028] Example 1 See Figure 1 , Figure 1 This is a schematic flowchart illustrating a method for allocating carbon emission reduction contributions from a virtual power plant, as provided in an embodiment of the present invention. The method includes steps 101 to 105, as detailed below: Step 101: Obtain the first operating data before the virtual power plant responds, and calculate the first node carbon potential and first load carbon flow rate of each node based on the first operating data to generate the first carbon emission flow distribution; In this embodiment, the step of acquiring the first operating data before the virtual power plant responds, and calculating the first node carbon potential and first load carbon flow rate of each node based on the first operating data to generate the first carbon emission flow distribution includes: The first operating data of the power grid before the response is obtained, including the topology, the active power flow of the first branch, the first active power output of each generator set, the carbon emission intensity of each generator set, and the first load power of each node. Based on the first active power output of each generator set and its corresponding carbon emission intensity, calculate the first carbon flow rate injected into the grid by each generator set. Based on the aforementioned topology, the first carbon flow rate injected into the power grid by each generator set, and the active power flow of the first branch, the first node carbon potential of each node is calculated. Calculate the first load carbon flow rate of each node based on the first load power and the first node carbon potential. The first carbon emission flow distribution is generated based on the first node carbon potential and the first load carbon flow rate of all nodes.

[0029] In this embodiment, when acquiring the initial operating data of the power grid before the response, the system collects first operating data from the power grid dispatching system, virtual power plant operation platform, energy management system, smart meters, distributed resource control terminal and carbon emission factor database. The first operating data includes topology, active power flow of each branch, active power output of each generator set and its corresponding carbon emission intensity, and load power of each node.

[0030] In this embodiment, the power grid has N nodes, M branches, and G generator sets. The virtual power plant contains K distributed resources. The active power output of the g-th generator set at time t is expressed as... The carbon emission intensity of the g-th generator unit is expressed as: The regulation power of the k-th DER at time t is expressed as: .

[0031] In this embodiment, the first carbon flow rate of each generator set is calculated based on its first active power output and corresponding carbon emission intensity. Specifically, the injected carbon flow rate of the g-th generator set at time t is: (1) in, This represents the carbon flow rate injected into the grid by the g-th generator unit at time t, and the unit can be kgCO2 / h; This represents the active power output of the unit at time t; This indicates the carbon emission intensity per unit of electricity generated by the unit. The carbon emission intensity of the power generation process is added to the power output, giving each megawatt of active power a carbon emission attribute label. The first carbon flow rate serves as the source of carbon flow transmission across the entire network; the carbon potential of all subsequent nodes originates from this source.

[0032] Subsequently, based on the aforementioned topology, the first carbon flow rate injected into the grid by each generator set, and the active power flow of the first branch, the first node carbon potential of each node is calculated.

[0033] In this embodiment, the calculation of the first node carbon potential of each node based on the topology, the carbon flow rate injected into the grid by each generator set, and the active power flow of the branch includes: The carbon flow rate injected into the power grid by each generator set is used as the initial carbon flow source. Along the flow direction of the active power flow of the branch, the carbon flow rate is transmitted to each branch and node of the power grid in a step-by-step manner according to the preset power distribution ratio. For each node, the first node carbon potential is calculated based on the sum of all carbon flow rates flowing into the node and the total active power flowing into the node.

[0034] In this embodiment, for any node i, the carbon potential of node i is determined by two parts: one part comes from the carbon flow flowing in from upstream nodes with the tidal current, and the other part comes from the carbon flow injected by local generator sets. Dividing the total carbon flow flowing into node i by the total power flowing into node i yields the carbon emission intensity per unit of electricity at that node.

[0035] In this embodiment, the set of upstream nodes of node i that flows into node i is determined by the topology. Then, based on the set of upstream nodes Including several upstream nodes j, the carbon potential of the first node before the node response is expressed as: (2) in, This represents the first node carbon potential of node i at time t before the response; Let i be the set of upstream nodes of node i. This indicates the active power flow responding to the preceding branch j to i; This represents the nodal carbon potential of upstream node j; This represents the set of generator sets connected to node i; This represents the active power output of the g-th generating unit before the response.

[0036] In this embodiment, the carbon flow rate injected into the grid by each generator unit is used as the initial carbon flow source. Along the active power flow direction of the branches, the carbon flow rate is progressively transferred to each branch and node of the grid according to the power distribution ratio. This ensures that the carbon flow carried by each active power in the grid is distributed according to its actual flow path, rather than using a statistical average to allocate carbon responsibility. Based on this, for each node, the node carbon potential is calculated based on all carbon flow rates flowing into that node and the total active power flowing into that node. This ensures that the carbon potential per unit of electricity at that node accurately reflects the weighted average result of the carbon flow flowing into that node. This progressive transfer method based on power ratio allocation fully preserves the dynamic migration characteristics of carbon flow with power flow distribution, enabling the node carbon potential to respond sensitively to changes in grid operation mode. It provides an accurate and physically consistent node carbon potential input for subsequent calculations of the carbon flow difference before and after the response.

[0037] In this embodiment, after obtaining the first node carbon potential of each node, the load power of each node is multiplied by the corresponding node carbon potential to obtain the load carbon flow rate of that node: (3) in, This represents the load carbon flow rate of node i before the response; This represents the load power of node i before the response.

[0038] In this embodiment, the first load carbon flow rate represents the real-time carbon emission rate undertaken by the node before load response. It reflects both the magnitude of the load and the power structure characteristics of the load's location. Finally, the first node carbon potential data and the first load carbon flow rate data of all nodes are summarized to form the first carbon emission flow distribution before response, which serves as a benchmark for subsequent evaluation of the virtual power plant's response effect.

[0039] In this embodiment, by acquiring the grid topology, active power flow of the first branch, the first active power output of each generator set and its corresponding carbon emission intensity, and the first load power of each node before the response, the first carbon flow rate injected into the grid by each generator set is calculated based on the correspondence between the output of each generator set and its carbon emission intensity. This maps the carbon emission attributes of the generation side to the grid power injection end in the form of carbon flow rate. Based on this, the first node carbon potential of each node is calculated using the topology, the first carbon flow rate injected by each generator set, and the active power flow of the first branch. This ensures that the carbon potential of each node is determined based on both upstream carbon flow injection and local generation carbon flow injection, avoiding the spatial difference neglect problem caused by using a uniform carbon emission factor. Furthermore, the first load carbon flow rate of each node is calculated based on the first load power and the first node carbon potential, thereby transforming the node carbon potential into the actual carbon emission responsibility on the load side. This provides a node-level fine-grained ground-state data foundation for subsequent comparison of carbon emission flows before and after the response.

[0040] Step 102: Obtain the second operating data after the virtual power plant responds, and calculate the second carbon emission flow distribution based on the second operating data; In this embodiment, obtaining the second operating data after the virtual power plant's response, and calculating the second carbon emission flow distribution based on the second operating data, includes: After obtaining the response, the second operating data of the power grid includes the topology, the active power flow of the second branch, the second active power output of each generator set, the carbon emission intensity of each generator set, and the second load power of each node. Based on the second active power output of each generator set and its corresponding carbon emission intensity, the second carbon flow rate injected into the grid by each generator set is calculated. Based on the aforementioned topology, the second carbon flow rate injected into the grid by each generator set, and the active power flow of the second branch, the second node carbon potential of each node is calculated. Calculate the second load carbon flow rate of each node based on the second load power and the second node carbon potential. The second carbon emission flow distribution is generated based on the second node carbon potential and the second load carbon flow rate of all nodes.

[0041] In this embodiment, after the virtual power plant completes a response, its response behavior is transformed into a calculable power change sequence. Post-response operational data is then retrieved from the grid dispatching side, including the topology, active power flow of the second branch, the second active power output of each generator unit and its corresponding carbon emission intensity, and the second load power of each node. The difference between this data and the initial operational data before the response is that it already includes the changes in grid operating status caused by the virtual power plant's response behavior. Changes in grid connection power alter the injected power of local nodes, leading to a redistribution of power flow in surrounding branches, and potentially adjusting the output of some generator units. However, the topology typically remains unchanged before and after this process. The virtual power plant's response behavior does not alter the physical connections of the grid; it only changes the active power distribution of each branch and the output setpoints of each generator unit.

[0042] In this embodiment, let the virtual power plant access node be b, and its pre-response grid connection power be expressed as: The power at the grid connection point after response is expressed as Then the change in power response of the virtual power plant at time t is: (4) in, This represents the net response power of the virtual power plant to the grid at time t. If this value is greater than zero, it indicates that the virtual power plant provides positive regulation to the grid by increasing output or decreasing power consumption; if this value is less than zero, it indicates that the virtual power plant increases power consumption or forms regulation opposite to the response objective.

[0043] The virtual power plant contains K distributed resources. The actual adjustment amount of the k-th resource at time t is... The overall response power of the virtual power plant and the internal resource adjustment amount satisfy the following: (5) This formula indicates that the total response power generated by the virtual power plant's grid connection point is constituted by the combined regulation behavior of all internal DERs.

[0044] With the second set of operational data following the response, the virtual power plant response alters the power exchange relationship at the grid connection point. Therefore, the response power needs to be incorporated as a nodal power change into the recalculation of grid power flow and carbon emission flow. The virtual power plant response behavior is equivalent to the injected power change at grid connection point b. The equivalent power of node b after the response is then expressed as: (6) in, This represents the equivalent power of node b before the response; This represents the equivalent power of node b after the response; This represents the change in power response of the virtual power plant.

[0045] For the g-th generator set, its second carbon flow rate after response is The carbon emission intensity of each generator unit remains unchanged due to the response event, maintaining the same inherent emission characteristics as before the response. The calculation of the nodal carbon potential after the response then follows. For node i, the nodal carbon potential after the response is the sum of all carbon flow rates flowing into that node divided by the total active power flowing into that node, expressed as: (7) in, This represents the nodal carbon potential of node i after the response; This represents the active power flow from branch j to i after the response; This represents the output of the g-th generator unit after the response. The calculation logic of this formula is completely consistent with the carbon potential of the first node before the response, the only difference being that all input data comes from the operating state after the response.

[0046] In this embodiment, the load carbon flow rate of node i after the response is further calculated as follows: (8) in, This represents the load carbon flow rate at node i after the response; This represents the load power of node i after the response.

[0047] In this embodiment, the system obtains the carbon potential and load carbon flow rate of each node after the response by recalculating the carbon emission flow. The difference between the results before and after the response reflects the actual impact of the virtual power plant's response behavior on the grid carbon flow distribution. Finally, the second node carbon potential data and the second load carbon flow rate data of all nodes are summarized to form the second carbon emission flow distribution. Using the exact same calculation rules as before the response essentially establishes a comparable reference benchmark for subsequent difference comparisons. If the two sets of calculations are inconsistent in methodology, then any difference cannot be attributed to the response behavior of the virtual power plant itself.

[0048] In this embodiment, after the virtual power plant completes its response, the topology of the power grid after the response, the active power flow of the second branch, the second active power output of each generator unit and its corresponding carbon emission intensity, and the second load power of each node are obtained. Then, the second carbon flow rate injected by each generator unit, the second node carbon potential of each node, and the second load carbon flow rate of each node are calculated, thereby generating the second carbon emission flow distribution. Since a unified carbon flow tracking method and the same calculation rules are used before and after the response, the difference between the two calculation results only stems from the changes in the power grid operating state caused by the virtual power plant's response behavior, resulting in good attribution consistency in the comparison of carbon flow distribution before and after the response. Simultaneously, the power flow data after the response naturally contains the impact of the virtual power plant's response behavior on the global distribution of carbon flow in the power grid, providing a complete physical causal chain for subsequent emission reduction contribution calculations.

[0049] In another optional embodiment, the system collects multi-source data from the power grid dispatching system, virtual power plant operation platform, energy management system, smart meters, distributed resource control terminals, and carbon emission factor database. This multi-source data includes first-stage operating data before the response and second-stage operating data after the response, specifically including power grid topology, node load power, branch active power flow, generator active power output, generator carbon emission intensity, virtual power plant grid connection point power, response command power, actual response power, response start and end times, and the operating power and regulation of each DER within the virtual power plant. Furthermore, the collected data undergoes outlier removal, missing value completion, timestamp alignment, unified sampling intervals, unified power direction, and unified carbon emission units to form virtual power plant response event samples. (9) in, Represents the response time window for the i-th response event; This indicates the virtual power plant's grid connection point power before the response; This indicates the virtual power plant's grid connection power after the response; Indicates the power of the scheduling command; This indicates the actual response power of the virtual power plant; This represents the active power flow from branch i to j.

[0050] In this embodiment, after obtaining virtual power plant response event samples, the first carbon emission flow distribution and the second carbon emission flow distribution are calculated. Then, the difference in total load carbon flow rate is calculated based on the first carbon emission flow distribution and the second carbon emission flow distribution, and the initial value of carbon emission reduction contribution is calculated based on the difference in total load carbon flow rate.

[0051] Step 103: Calculate the difference in total load carbon flow rate based on the first carbon emission flow distribution and the second carbon emission flow distribution, and calculate the initial value of carbon emission reduction contribution based on the difference in total load carbon flow rate; In this embodiment, the step of calculating the difference in total load carbon flow rate based on the first carbon emission flow distribution and the second carbon emission flow distribution, and calculating the initial value of carbon emission reduction contribution based on the difference in total load carbon flow rate, includes: The first load carbon flow rate of each node is obtained based on the first carbon emission flow distribution, and the pre-response load carbon flow rate is obtained by summing the first load carbon flow rates of all nodes. The second load carbon flow rate of each node is obtained based on the second carbon emission flow distribution, and the load carbon flow rate after response is obtained by summing the second load carbon flow rates of all nodes. Calculate the load carbon flow rate difference between the pre-response load carbon flow rate and the post-response load carbon flow rate; The initial value of the carbon emission reduction contribution is calculated based on the response time of the virtual power plant and the difference in load carbon flow rate.

[0052] In this embodiment, after calculating the carbon emission flow distribution twice, before and after the response, the pre-response load carbon flow rate of all nodes is extracted from the first carbon emission flow distribution. Extracting the response afterload carbon flow rate of all nodes from the second carbon emission flow distribution. Response preload carbon flow rate The load carbon flow rate represents the total carbon emission rate borne by the electrical load before the response occurs, and the load carbon flow rate after the response. The difference between the two totals directly reflects the net change in the carbon emission responsibility of the grid load side caused by the virtual power plant's response behavior. Therefore, the load carbon flow rate difference is specifically: (10) in, This represents the difference in carbon flow rate on the load side of the system before and after the response at time t; This represents the load carbon flow rate of node i before the response; This represents the load carbon flow rate at node i after the response. When When the response time is lower than the pre-response carbon flow rate on the load side, it indicates that the virtual power plant's response at that moment produced an actual emission reduction effect. When the response occurs, it indicates that the carbon flow rate on the load side of the system is higher than before the response. This response has not produced effective emission reduction, or it has increased the carbon emission pressure of the system during this period. In other words, the response has actually increased the carbon emission pressure of the system at this moment.

[0053] In this embodiment, after obtaining the carbon flow rate difference at each sampling time, these differences are accumulated over time over the entire response period T of the virtual power plant. For the time interval Δt between two adjacent sampling points, ΔRsys(t) at that time is multiplied by Δt to obtain the total change in the system load carbon flow rate during that time interval. These changes are then accumulated over the entire response period to obtain the initial value of the carbon emission reduction contribution of the virtual power plant. Specifically: (11) in, This indicates the initial carbon emission reduction contribution of the virtual power plant; This indicates the time interval between adjacent sampling points.

[0054] In this embodiment, the changes in system carbon flow caused by the virtual power plant response at each sampling moment are accumulated over the response period to form the total emission reduction corresponding to the response event. This takes into account the changes in carbon flow at every moment during the response process. Regardless of whether the response power is stable or fluctuating, or whether the response duration is long or short, all information is completely preserved in the final result. This avoids the coarse processing of using a single moment's state to represent the entire response process, making the subsequent contribution assessment more consistent with the actual response process.

[0055] In another alternative embodiment, to enhance engineering applicability, the initial contribution of grid-connected node b can be weighted based on the carbon potential of the first node before the response and the carbon potential of the second node after the response, specifically: (12) in, This represents the carbon potential of the first node of the virtual power plant b before the response; This represents the second node carbon potential of the virtual power plant grid connection point b after the response.

[0056] In this embodiment, the response power of the virtual power plant, combined with the carbon potential of its node, reflects the carbon reduction value corresponding to that response power. Using the average node carbon potential before and after the response reduces the impact of single-state carbon potential fluctuations on the calculation results.

[0057] In this embodiment, the total system load carbon flow rate before the response is obtained by summing the first load carbon flow rates of all nodes, and the total system load carbon flow rate after the response is obtained by summing the second load carbon flow rates of all nodes. Subtracting the two yields the load carbon flow rate difference, which directly measures the net change in the total carbon emission responsibility of the grid load side caused by the virtual power plant's response behavior. Based on this, the difference is accumulated over time in conjunction with the response duration to obtain the initial value of the total carbon emission reduction brought to the grid by the virtual power plant throughout the entire response event. Since the reduction in the total system load carbon flow rate means a real decrease in the overall carbon emission pressure of the grid, this method of calculating the initial contribution based on the change in global load carbon flow rate provides a macroscopic verification basis for the emission reduction contribution of the virtual power plant based on the change in the carbon flow of the entire grid.

[0058] Step 104: Statistically analyze the response time, response deviation, and carbon potential sensitivity of the virtual power plant; calculate the correction coefficient based on the response time, response deviation, and carbon potential sensitivity; and correct the initial value of the carbon emission reduction contribution based on the correction coefficient to obtain the effective carbon emission reduction contribution. In this embodiment, the response time, response deviation, and carbon potential sensitivity of the statistical virtual power plant are analyzed. A correction coefficient is calculated based on the response time, response deviation, and carbon potential sensitivity. The initial value of the carbon emission reduction contribution is then corrected based on the correction coefficient to obtain the effective carbon emission reduction contribution. This includes: The response time of the virtual power plant is statistically analyzed, and a response time correction parameter is calculated based on the response time. Obtain the dispatch command power curve and the actual response power curve of the virtual power plant, calculate the response deviation based on the dispatch command power curve and the actual response power curve, and calculate the response reliability correction coefficient based on the response deviation; The nodal carbon potential change at the grid connection point of the virtual power plant is statistically analyzed. Based on the nodal carbon potential change and the total response power, the carbon potential sensitivity is calculated. Based on the ratio of the carbon potential sensitivity to the maximum carbon potential sensitivity in the preset area, the carbon potential sensitivity correction coefficient is calculated. The initial value of the carbon emission reduction contribution is corrected based on the response time correction coefficient, response reliability correction coefficient, and carbon potential sensitivity correction coefficient to obtain the effective carbon emission reduction contribution.

[0059] In this embodiment, the impact of the virtual power plant's response behavior on the grid's carbon emission flow depends not only on the magnitude of the response power but also on the timeliness of the response, the accuracy of execution, and the sensitivity of the response location to carbon potential. For example, if two virtual power plants respond with the same power, but one responds quickly and stably while the other responds with a delayed response and a large execution deviation, their actual values ​​are clearly different. Therefore, after calculating the initial value of the carbon emission reduction contribution, it is necessary to correct the initial value of the carbon emission reduction contribution from three dimensions: response time, response deviation, and carbon potential sensitivity.

[0060] In this embodiment, the response time includes the response command issuance time, the actual response start time, the scheduling request response duration, and the actual continuous response duration; the step of statistically analyzing the response time of the virtual power plant and calculating response time correction parameters based on the response time includes: Calculate the time difference between the time the response instruction is issued and the actual response start time. Based on the time difference and the proportion of the scheduling requirement response time, calculate the response speed correction value. Calculate the response duration correction value based on the ratio of the actual continuous response duration to the scheduled response duration. The response time correction parameter is obtained by weighted summing of the response speed correction value and the response duration correction value.

[0061] In terms of response time, the system first obtains the time when the response command was issued. The actual start response time of the virtual power plant Scheduling requires response time Actual continuous response time Scheduling requirements duration .

[0062] In this embodiment, firstly, based on the response command issuance time... The actual start response time of the virtual power plant Scheduling requires response time Calculate the response speed correction value Specifically: (13) In this embodiment, the closer the response is to the time the instruction is issued, the higher the speed correction value; if the delay time exceeds the response window allowed by the scheduling, this correction value is reduced to zero.

[0063] In this embodiment, the response maintenance capability of the virtual power plant is measured by calculating a persistence correction coefficient. A coefficient of 1 is used when the actual continuous response duration meets or exceeds the dispatch requirement; otherwise, it is reduced by the proportion of the actual duration to the required duration. Specifically: (14) in, This is a continuous correction factor.

[0064] In this embodiment, the response time correction coefficient is obtained by weighted summing of the speed correction value and the persistence correction value. Specifically: (15) in, and The weights are preset and the sum of the two is 1. In actual use, the weights can be flexibly adjusted according to the scheduling agency's emphasis on response speed and sustainability.

[0065] In this embodiment, a response speed correction value is calculated based on the ratio of the time difference between the response command issuance time and the actual response start time to the required response time under scheduling. This value directly reflects the agility of the virtual power plant in responding to scheduling commands. A response duration correction value is calculated based on the ratio of the actual continuous response time to the required response time under scheduling. This value reflects the virtual power plant's response maintenance capability. After weighted summing the two correction values ​​to obtain the response time correction parameter, the response time correction parameter can simultaneously evaluate the two timeliness factors of response agility and response duration, effectively distinguishing between two different response qualities: rapid response but midway exit and stable and continuous completion of the response.

[0066] In this embodiment, the power curve obtained from the dispatch command originates from the demand response command issued by the power grid dispatch system. During the actual operation of the virtual power plant participating in demand response, the dispatching agency determines the target power value and response period required for this response based on the power grid load balancing demand and peak-shaving pressure, and issues the command to the virtual power plant operation platform. This command is typically given in the form of a power time series, i.e., the target power value corresponding to each sampling point within the response period, serving as a benchmark for the virtual power plant's response execution. The actual response power curve of the virtual power plant originates from the actual power measurement data at the grid connection point. During the response process, the virtual power plant operation platform continuously collects actual power values ​​at a fixed sampling frequency through the metering device at the grid connection point, forming an actual power time series within the response period. By comparing these values ​​point-by-point on the same time coordinate, the execution deviation at each moment can be obtained. It should be noted that the actual response power curve reflects the overall net power change of the virtual power plant at the grid connection point, which already incorporates the sum of the effects of all internal distributed resource regulation behaviors. A complete actual response power curve typically needs to be recorded starting from the stable operating state before the response, throughout the entire response execution process, until the power returns to stability after the response ends. Only in this way can the power change characteristics of the entire response initiation, continuous execution, and exit recovery stages be fully captured.

[0067] In terms of response deviation, response reliability is reflected by the response deviation between the scheduling command power curve and the actual response power curve. Specifically: (16) in, This indicates the degree of deviation between the actual response curve and the dispatch command curve. The smaller the deviation, the better the virtual power plant's performance.

[0068] Then, the response reliability correction coefficient is determined based on the response deviation, specifically: (17) In this embodiment, if the actual response is highly consistent with the scheduling command, the smaller the deviation rate, the higher the response reliability correction coefficient. The coefficient is close to 1; if the response deviation is large, the larger the deviation rate, the lower the coefficient, and the response reliability correction coefficient is... The correction factor should be reduced; when the deviation exceeds the reasonable range, the minimum correction factor should be 0.

[0069] In this embodiment, the carbon potential of the first node before the grid connection point response is obtained in terms of carbon potential sensitivity. and the second node carbon potential after response The difference between the two is calculated to obtain the change in nodal carbon potential at the grid connection point. : (18) Then, the carbon potential sensitivity is calculated based on the change in nodal carbon potential combined with the total response power. Specifically: (19) in, Carbon potential sensitivity measures the degree of change in carbon potential at the grid connection point caused by a unit response power. If the virtual power plant response has a significant impact on the carbon potential at the grid connection point, then the carbon potential sensitivity is... Relatively high.

[0070] Furthermore, the carbon potential sensitivity is normalized by the ratio of the carbon potential sensitivity to the maximum carbon potential sensitivity in the preset region, thereby calculating the carbon potential sensitivity correction coefficient. Specifically: (20) in, This is the maximum carbon potential sensitivity for the preset region.

[0071] In this embodiment, correction parameters are constructed from three dimensions: response time, response deviation, and carbon potential sensitivity. First, the response time correction parameter is calculated based on the response time to evaluate the timeliness of the virtual power plant's response to dispatch instructions. Next, the response reliability correction coefficient is calculated based on the deviation between the dispatch instruction power curve and the actual response power curve to evaluate the execution accuracy of the virtual power plant. Finally, the carbon potential sensitivity is calculated based on the change in carbon potential at the grid connection point node combined with the total response power, and a carbon potential sensitivity correction coefficient is calculated based on the ratio of the carbon potential sensitivity to the maximum carbon potential sensitivity in the preset area to evaluate the actual impact of the response behavior on the grid's carbon potential. These three correction parameters respectively cover the efficiency characteristics, accuracy characteristics, and carbon emission reduction effect characteristics of the virtual power plant's response. After applying the three correction coefficients together to the initial contribution value, response behaviors with fast response speed, small execution deviation, and high carbon potential sensitivity can obtain a higher effective contribution, while response behaviors with lag, large deviation, or low carbon potential sensitivity are reasonably reduced, so that the final effective contribution can truly reflect the comprehensive value of the virtual power plant's response behavior.

[0072] In this embodiment, the step of correcting the initial value of the carbon emission reduction contribution based on the response time correction coefficient, response reliability correction coefficient, and carbon potential sensitivity correction coefficient to obtain the effective carbon emission reduction contribution includes: The response time correction coefficient, response reliability correction coefficient, and carbon potential sensitivity correction coefficient are weighted and summed based on preset weights to obtain a comprehensive correction coefficient. The effective carbon emission reduction contribution is determined by multiplying the initial value of the carbon emission reduction contribution with the comprehensive correction coefficient.

[0073] In this embodiment, after the three correction coefficients are calculated independently, the system uses preset weights. , , The three factors are weighted and summed to obtain the comprehensive correction coefficient. : (twenty one) in, This represents the overall correction factor; This represents the response time correction factor; This represents the response reliability correction factor; This represents the carbon potential sensitivity correction factor; , , Let each represent the weight of the correction factor, and satisfy the following condition: (twenty two) In this embodiment, the final comprehensive correction coefficient is used to determine the effective carbon emission reduction contribution of the virtual power plant by combining the initial value of the carbon emission reduction contribution with the comprehensive correction coefficient. Specifically: (twenty three) in, This represents the effective carbon emission reduction contribution of the virtual power plant. The contribution value, after quality screening and reduction, retains the results calculated based on physical carbon flows while also incorporating response execution quality and spatial sensitivity information.

[0074] In this embodiment, a comprehensive correction coefficient is obtained by weighting and summing the response time correction coefficient, response reliability correction coefficient, and carbon potential sensitivity correction coefficient using preset weights. The weighting configuration allows for flexible adjustment of the influence of each dimension in the comprehensive evaluation, adapting to the evaluation emphasis requirements of different application scenarios. Based on this, the initial value of carbon emission reduction contribution is multiplied by the comprehensive correction coefficient to determine the effective carbon emission reduction contribution. This ensures that the final effective contribution of each response event is positively correlated with its overall response quality, providing a reasonable allocation base that has undergone quality screening and value correction for subsequent internal resource contribution allocation.

[0075] Step 105: Based on the adjustment amount of each distributed resource, the carbon potential of the first node of the node, and the response quality of each distributed resource, the effective carbon emission reduction contribution is allocated to each distributed resource to obtain the carbon emission reduction contribution corresponding to each distributed resource.

[0076] In this embodiment, the allocation of the effective carbon reduction contribution to each distributed resource based on the adjustment amount of each distributed resource, the carbon potential of the first node of the node where it is located, and the response quality of each distributed resource, to obtain the carbon reduction contribution corresponding to each distributed resource, includes: Based on the resource type, adjustment direction, and adjustment amount of each distributed resource, determine the effective emission reduction adjustment amount of each distributed resource; Based on the effective emission reduction adjustment amount of each distributed resource, the carbon potential of the first node of the node where it is located, and the response time, the basic contribution value of each distributed resource is calculated, and the basic contribution values ​​of all distributed resources are summed to obtain the total basic contribution value. Based on the individual response time, individual execution deviation, and node carbon potential level of each distributed resource, the basic contribution value and the total basic contribution value of each distributed resource are corrected to obtain the corrected contribution value and the total corrected contribution value of each distributed resource. The allocation weight of each distributed resource is determined based on the ratio between the correction contribution value of each distributed resource and the total correction contribution value of the distributed resources. The effective carbon emission reduction contribution is allocated based on the allocation weight to obtain the carbon emission reduction contribution corresponding to each distributed resource.

[0077] In this embodiment, after the correction of the overall effective carbon emission reduction contribution of the virtual power plant is completed, the final contribution of each resource should be positively correlated with its actual adjustment effect, the carbon potential level of its location, and the quality of its individual execution.

[0078] In this embodiment, all K distributed resources are first traversed, and for each distributed resource k, adjustments are made according to its resource type, adjustment direction, and adjustment amount. Determine the effective emission reduction adjustment amount .

[0079] In this embodiment, the processing rules differ for different types of resources: When photovoltaic resources increase their output, a positive response is generated, and the effective emission reduction adjustment is directly taken. The positive part, that is: (twenty four) When controllable load reduces electricity consumption, a positive response is generated, and the effective emission reduction adjustment amount is taken as the positive value of the opposite of the adjustment amount, that is: (25) Energy storage resources need to be statistically analyzed separately for discharge and charging periods. For energy storage resources, if their discharge supports the power grid, the effective emission reduction regulation is: (26) Charging energy storage resources itself does not directly contribute to emission reduction. However, if it charges during low-carbon periods and discharges during high-carbon periods, it creates an emission reduction effect across time periods. Therefore, the positive regulation during the energy storage discharge period and the electricity consumption during the charging period are included in the calculation. The net effective regulation is determined by deducting the carbon flow cost of charging from the discharge contribution.

[0080] In this embodiment, the basic contribution of a resource is determined by its effective regulation power, the carbon potential of its node, and the duration of its response. The greater the resource regulation, the higher the carbon potential of its node, and the longer the duration, the higher its basic contribution. Therefore, the basic contribution value of each resource k is... : (27) in, This represents the base contribution value of the k-th resource; This represents the effective emission reduction regulation power of the k-th resource at time t; Indicates the node where the k-th resource is located. The response to the carbon potential at the preceding node, The sampling interval is denoted as .

[0081] In this embodiment, charging of energy storage resources results in a reverse power change. However, if it charges during low-carbon periods and discharges during high-carbon periods, it can contribute to emission reduction across time periods. In this case, discharging during high-carbon periods can make a positive contribution, while charging during low-carbon periods incurs energy transfer costs. Subtracting the two yields the net basic contribution of energy storage. (28) in, This is the energy storage discharge period; This is the period for charging energy storage; This refers to the energy storage discharge power; For energy storage charging power, The sampling interval is denoted as .

[0082] In this embodiment, in most cases, allocation based solely on the basic contribution value is sufficient to reflect the differences in resource adjustment amount and spatial carbon potential level. Therefore, after obtaining the basic contribution value of each distributed resource and the total basic contribution value of all distributed resources, the allocation weight of each distributed resource is calculated: (29) in, This represents the contribution allocation weight of the k-th resource.

[0083] Ultimately, the carbon emission reduction contribution allocated to the k-th resource is: (30) In another optional embodiment, in certain application scenarios, the collaborative cooperation among the distributed resources within the virtual power plant can generate additional emission reduction effects. This synergistic effect is not simply additive. For example, when energy storage and photovoltaics respond simultaneously, energy storage can absorb the fluctuating output of photovoltaics, making the overall response curve smoother and more stable. To this end, this embodiment also provides an improved Shapley value allocation method to allocate the effective carbon emission reduction contribution to each distributed resource, thereby obtaining the corresponding carbon emission reduction contribution of each distributed resource.

[0084] The Shapley value allocation method begins by defining a contribution function for any combination of resources. Let's assume the virtual power plant contains K distributed resources, forming the total resource set. ,in Let K be the total number of resources. For any subset of resources... Its contribution to carbon emission reduction It is determined jointly by all resources within this subset, specifically: (31) in, The total regulation power of subset S at time t is: (32) Since the same amount of adjustment power produces completely different emission reduction effects at high carbon potential nodes and low carbon potential nodes, this embodiment also needs to introduce a subset of weighted node carbon potentials. : (33) in, This represents the comprehensive response correction coefficient of subset S.

[0085] In this embodiment, the total regulation power, weighted node carbon potential, sampling interval Δt, and subset comprehensive response correction coefficient are used. Multiplying these four factors together and summing them over the response time T yields the contribution function value of subset S. It should be noted that... The calculation method is similar to the overall correction coefficient of the virtual power plant, but it only performs statistics on the resources contained in the subset, that is, it only uses the response time parameters, execution deviation data and node carbon potential data of the resources in subset S.

[0086] In this embodiment, after obtaining the contribution function of any subset, the Shapley value of each resource can be calculated. In this embodiment, the contribution of the k-th resource is not only considered in terms of its individual adjustment amount, but also in the incremental contribution to overall emission reduction after being added to different resource combinations. By traversing different resource combinations, the marginal effect of the resource in the coordinated response of the virtual power plant can be evaluated more fairly. For the k-th resource, its traditional Shapley value... Specifically: (34) In this embodiment, This represents the marginal carbon emission reduction contribution brought about by adding the k-th resource to resource combination S. The weighting coefficients are... The Shapley value reflects the probability weight of resource k when it is added to subsets of different sizes. Larger subsets result in smaller fluctuations in the marginal contribution of a newly added resource, and the weight decreases accordingly. By traversing all possible resource combinations, the Shapley value fairly evaluates the marginal contribution of each resource in various collaborative scenarios, rather than simply looking at its independent moderating amount. For example, a resource may not be particularly effective when responding alone, but when combined with another resource, it can significantly reduce the overall response deviation; this collaborative gain can be reflected in the incremental marginal contribution.

[0087] After obtaining the traditional Shapley values ​​for each resource, the system also needs to consider the quality of individual responses. Individual correction coefficients for each resource are required. It is a weighted composite of three components: individual response time, individual execution bias, and node carbon potential level.

[0088] In this embodiment, the individual response time includes the actual start time of the response. Based on the actual start response time and delay exceeding the scheduling requirement duration. Calculate the response time coefficient to measure the timeliness of resource activation. The response time coefficient for the k-th resource is: (35) In this embodiment, the closer the actual response start time is to the command issuance time... The higher the response time coefficient, the longer the delay will be if it exceeds the scheduling requirement. Then it returns to zero.

[0089] In this embodiment, the response reliability coefficient is calculated based on the degree of deviation between the resource execution curve and the instruction curve. Specifically: (36) like If the value is less than 0, the response reliability coefficient is 0; otherwise, the response reliability coefficient is... .

[0090] In this embodiment, the nodal carbon potential coefficient Combining the carbon potential level of the node where the resource is located with the adjustment amount, specifically: (37) In this embodiment, under the same response power conditions, resources located at high carbon potential nodes or high carbon potential periods have higher emission reduction value, thus obtaining higher node carbon potential correction results.

[0091] The three coefficients evaluate the response quality of individual resources from the perspectives of response efficiency, execution accuracy, and emission reduction value.

[0092] In this embodiment, the individual correction coefficient is calculated by weighting the response time coefficient, response reliability coefficient, and nodal carbon potential coefficient. Specifically: (38) in, This represents the individual correction coefficient for the k-th resource; This represents the response time coefficient of the resource; This indicates the response reliability coefficient of the resource; This represents the nodal carbon potential coefficient of the resource; , , Let be the weighting coefficient, and satisfy: .

[0093] In this embodiment, the corrected Shapley value is obtained by multiplying the individual correction factor by the traditional Shapley value of the corresponding resource: (39) After normalizing the corrected Shapley value, the final carbon emission reduction contribution allocated to the k-th resource is: (40) in, The contribution of virtual power plants to effective carbon emission reduction. The improved Shapley value method retains the advantages of the Shapley value in evaluating collaborative marginal contributions, while introducing considerations for resource execution quality through individual correction coefficients. After allocation, a system verification is performed to ensure that the sum of all allocation results matches the total amount to be allocated. Compared to carbon potential weighted proportional allocation, the improved Shapley value method requires more data and computation, but it can provide fairer and more reasonable allocation results in scenarios with diverse resource types and complex collaborative interactions.

[0094] In this embodiment, the effective emission reduction adjustment amount of each distributed resource is first determined based on its resource type, adjustment direction, and adjustment amount. The basic contribution value of each resource is obtained by multiplying the effective emission reduction adjustment amount, the carbon potential of its node, and the response time, and then summed to obtain the total basic contribution value. This ensures that resources with large adjustment amounts and located in high-carbon-potential nodes receive higher basic contributions. Furthermore, the individual response time, individual execution deviation, and node carbon potential level of each resource are introduced to correct the basic contribution value and the total basic contribution value, resulting in corrected contribution values ​​and a corrected total contribution value for each resource. This allows resources with timely responses, accurate execution, and located in high-carbon-potential regions to receive additional gains in allocation. Finally, the allocation weight is determined based on the proportion of each resource's corrected contribution value in the total corrected contribution value, and the effective carbon emission reduction contribution is allocated accordingly. This ensures that the final contribution amount allocated to each resource reflects both its actual physical adjustment contribution and its differences in response quality and marginal emission reduction value, avoiding the incentive bias caused by allocation solely based on electricity or power.

[0095] Please refer to Figure 2 , Figure 2 A schematic diagram of a virtual power plant carbon emission reduction contribution allocation device provided in an embodiment of the present invention includes: a first carbon emission flow distribution calculation module 201, a second carbon emission flow distribution calculation module 202, a carbon emission reduction contribution initial value calculation module 203, a correction module 204, and an allocation module 205. The first carbon emission flow distribution calculation module 201 is used to acquire the first operating data before the virtual power plant responds, and calculate the first node carbon potential and the first load carbon flow rate of each node based on the first operating data to generate the first carbon emission flow distribution. The second carbon emission flow distribution calculation module 202 is used to obtain the second operating data after the virtual power plant responds, and calculate the second carbon emission flow distribution based on the second operating data; The carbon emission reduction contribution initial value calculation module 203 is used to calculate the difference in total load carbon flow rate based on the first carbon emission flow distribution and the second carbon emission flow distribution, and to calculate the initial value of carbon emission reduction contribution based on the difference in total load carbon flow rate. The correction module 204 is used to statistically analyze the response time, response deviation, and carbon potential sensitivity of the virtual power plant, calculate the correction coefficient based on the response time, response deviation, and carbon potential sensitivity, and correct the initial value of the carbon emission reduction contribution based on the correction coefficient to obtain the effective carbon emission reduction contribution. The allocation module 205 is used to allocate the effective carbon emission reduction contribution to each distributed resource based on the adjustment amount of each distributed resource, the carbon potential of the first node of the node where it is located, and the response quality of each distributed resource, so as to obtain the carbon emission reduction contribution corresponding to each distributed resource.

[0096] In this embodiment, the first carbon emission flow distribution calculation module is used to acquire first operating data before the virtual power plant responds, and calculate the first node carbon potential and first load carbon flow rate of each node based on the first operating data to generate the first carbon emission flow distribution, including: The first operating data of the power grid before the response is obtained, including the topology, the active power flow of the first branch, the first active power output of each generator set, the carbon emission intensity of each generator set, and the first load power of each node. Based on the first active power output of each generator set and its corresponding carbon emission intensity, calculate the first carbon flow rate injected into the grid by each generator set. Based on the aforementioned topology, the first carbon flow rate injected into the power grid by each generator set, and the active power flow of the first branch, the first node carbon potential of each node is calculated. Calculate the first load carbon flow rate of each node based on the first load power and the first node carbon potential. The first carbon emission flow distribution is generated based on the first node carbon potential and the first load carbon flow rate of all nodes.

[0097] In this embodiment, the first carbon emission flow distribution calculation module is used to calculate the first node carbon potential of each node based on the topology, the carbon flow rate injected into the grid by each generator set, and the active power flow of the branch, including: The carbon flow rate injected into the power grid by each generator set is used as the initial carbon flow source. Along the flow direction of the active power flow of the branch, the carbon flow rate is transmitted to each branch and node of the power grid in a step-by-step manner according to the preset power distribution ratio. For each node, the first node carbon potential is calculated based on the sum of all carbon flow rates flowing into the node and the total active power flowing into the node.

[0098] In this embodiment, the second carbon emission flow distribution calculation module is used to acquire second operating data after the virtual power plant responds, and calculate the second carbon emission flow distribution based on the second operating data, including: After obtaining the response, the second operating data of the power grid includes the topology, the active power flow of the second branch, the second active power output of each generator set, the carbon emission intensity of each generator set, and the second load power of each node. Based on the second active power output of each generator set and its corresponding carbon emission intensity, the second carbon flow rate injected into the grid by each generator set is calculated. Based on the aforementioned topology, the second carbon flow rate injected into the grid by each generator set, and the active power flow of the second branch, the second node carbon potential of each node is calculated. Calculate the second load carbon flow rate of each node based on the second load power and the second node carbon potential. The second carbon emission flow distribution is generated based on the second node carbon potential and the second load carbon flow rate of all nodes.

[0099] In this embodiment, the initial carbon emission reduction contribution calculation module is used to calculate the difference in total load carbon flow rate based on the first carbon emission flow distribution and the second carbon emission flow distribution, and to calculate the initial carbon emission reduction contribution based on the difference in total load carbon flow rate, including: The first load carbon flow rate of each node is obtained based on the first carbon emission flow distribution, and the pre-response load carbon flow rate is obtained by summing the first load carbon flow rates of all nodes. The second load carbon flow rate of each node is obtained based on the second carbon emission flow distribution, and the load carbon flow rate after response is obtained by summing the second load carbon flow rates of all nodes. Calculate the load carbon flow rate difference between the pre-response load carbon flow rate and the post-response load carbon flow rate; The initial value of the carbon emission reduction contribution is calculated based on the response time of the virtual power plant and the difference in load carbon flow rate.

[0100] In this embodiment, the correction module is used to statistically analyze the response time, response deviation, and carbon potential sensitivity of the virtual power plant, calculate a correction coefficient based on the response time, response deviation, and carbon potential sensitivity, and correct the initial value of the carbon emission reduction contribution based on the correction coefficient to obtain the effective carbon emission reduction contribution, including: The response time of the virtual power plant is statistically analyzed, and a response time correction parameter is calculated based on the response time. Obtain the dispatch command power curve and the actual response power curve of the virtual power plant, calculate the response deviation based on the dispatch command power curve and the actual response power curve, and calculate the response reliability correction coefficient based on the response deviation; The nodal carbon potential change at the grid connection point of the virtual power plant is statistically analyzed. Based on the nodal carbon potential change and the total response power, the carbon potential sensitivity is calculated. Based on the ratio of the carbon potential sensitivity to the maximum carbon potential sensitivity in the preset area, the carbon potential sensitivity correction coefficient is calculated. The initial value of the carbon emission reduction contribution is corrected based on the response time correction coefficient, response reliability correction coefficient, and carbon potential sensitivity correction coefficient to obtain the effective carbon emission reduction contribution.

[0101] In this embodiment, the correction module is used to correct the initial value of the carbon emission reduction contribution based on the response time correction coefficient, the response reliability correction coefficient, and the carbon potential sensitivity correction coefficient to obtain the effective carbon emission reduction contribution, including: The response time correction coefficient, response reliability correction coefficient, and carbon potential sensitivity correction coefficient are weighted and summed based on preset weights to obtain a comprehensive correction coefficient. The effective carbon emission reduction contribution is determined by multiplying the initial value of the carbon emission reduction contribution with the comprehensive correction coefficient.

[0102] In this embodiment, the response time includes the response command issuance time, the actual response start time, the scheduling request response duration, and the actual continuous response duration; the correction module is used to statistically analyze the response time of the virtual power plant and calculate response time correction parameters based on the response time, including: Calculate the time difference between the time the response instruction is issued and the actual response start time. Based on the time difference and the proportion of the scheduling requirement response time, calculate the response speed correction value. Calculate the response duration correction value based on the ratio of the actual continuous response duration to the scheduled response duration. The response time correction parameter is obtained by weighted summing of the response speed correction value and the response duration correction value.

[0103] In this embodiment, the allocation module is used to allocate the effective carbon emission reduction contribution to each distributed resource based on the adjustment amount of each distributed resource, the carbon potential of the first node of the node where it is located, and the response quality of each distributed resource, thereby obtaining the carbon emission reduction contribution corresponding to each distributed resource, including: Based on the resource type, adjustment direction, and adjustment amount of each distributed resource, determine the effective emission reduction adjustment amount of each distributed resource; Based on the effective emission reduction adjustment amount of each distributed resource, the carbon potential of the first node of the node where it is located, and the response time, the basic contribution value of each distributed resource is calculated, and the basic contribution values ​​of all distributed resources are summed to obtain the total basic contribution value. Based on the individual response time, individual execution deviation, and node carbon potential level of each distributed resource, the basic contribution value and the total basic contribution value of each distributed resource are corrected to obtain the corrected contribution value and the total corrected contribution value of each distributed resource. The allocation weight of each distributed resource is determined based on the ratio between the correction contribution value of each distributed resource and the total correction contribution value of the distributed resources. The effective carbon emission reduction contribution is allocated based on the allocation weight to obtain the carbon emission reduction contribution corresponding to each distributed resource.

[0104] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for allocating carbon emission reduction contributions from a virtual power plant, characterized in that, include: Obtain the first operating data before the virtual power plant responds, and calculate the first node carbon potential and first load carbon flow rate of each node based on the first operating data to generate the first carbon emission flow distribution; Obtain the second operating data after the virtual power plant responds, and calculate the second carbon emission flow distribution based on the second operating data; The difference in total load carbon flow rate is calculated based on the first carbon emission flow distribution and the second carbon emission flow distribution, and the initial value of carbon emission reduction contribution is calculated based on the difference in total load carbon flow rate. The response time, response deviation, and carbon potential sensitivity of the virtual power plant are statistically analyzed. Based on the response time, response deviation, and carbon potential sensitivity, a correction coefficient is calculated, and the initial value of the carbon emission reduction contribution is corrected based on the correction coefficient to obtain the effective carbon emission reduction contribution. Based on the adjustment amount of each distributed resource, the carbon potential of the first node of the node, and the response quality of each distributed resource, the effective carbon emission reduction contribution is allocated to each distributed resource to obtain the carbon emission reduction contribution corresponding to each distributed resource.

2. The method for allocating carbon emission reduction contributions from a virtual power plant as described in claim 1, characterized in that, The process of acquiring the first operational data before the virtual power plant responds, and calculating the first node carbon potential and first load carbon flow rate of each node based on the first operational data to generate the first carbon emission flow distribution, includes: The first operating data of the power grid before the response is obtained, including the topology, the active power flow of the first branch, the first active power output of each generator set, the carbon emission intensity of each generator set, and the first load power of each node. Based on the first active power output of each generator set and its corresponding carbon emission intensity, calculate the first carbon flow rate injected into the grid by each generator set. Based on the aforementioned topology, the first carbon flow rate injected into the grid by each generator set, and the active power flow of the first branch, the first node carbon potential of each node is calculated. Calculate the first load carbon flow rate of each node based on the first load power and the first node carbon potential of each node; The first carbon emission flow distribution is generated based on the first node carbon potential and the first load carbon flow rate of all nodes.

3. The method for allocating carbon emission reduction contributions from a virtual power plant as described in claim 2, characterized in that, The calculation of the first-node carbon potential of each node based on the topology, the carbon flow rate injected into the grid by each generator set, and the active power flow of the branches includes: The carbon flow rate injected into the power grid by each generator set is used as the initial carbon flow source. Along the flow direction of the active power flow of the branch, the carbon flow rate is transmitted to each branch and node of the power grid in a step-by-step manner according to the preset power distribution ratio. For each node, the first node carbon potential is calculated based on the sum of all carbon flow rates flowing into the node and the total active power flowing into the node.

4. The method for allocating carbon emission reduction contributions from a virtual power plant as described in claim 3, characterized in that, The step of obtaining the second operating data after the virtual power plant's response, and calculating the second carbon emission flow distribution based on the second operating data, includes: After obtaining the response, the second operating data of the power grid includes the topology, the active power flow of the second branch, the second active power output of each generator set, the carbon emission intensity of each generator set, and the second load power of each node. Based on the second active power output of each generator set and its corresponding carbon emission intensity, the second carbon flow rate injected into the grid by each generator set is calculated. Based on the aforementioned topology, the second carbon flow rate injected into the grid by each generator set, and the active power flow of the second branch, the second node carbon potential of each node is calculated. Calculate the second load carbon flow rate of each node based on the second load power and the second node carbon potential. The second carbon emission flow distribution is generated based on the second node carbon potential and the second load carbon flow rate of all nodes.

5. The method for allocating carbon emission reduction contributions from a virtual power plant as described in claim 4, characterized in that, The step of calculating the difference in total load carbon flow rate based on the first carbon emission flow distribution and the second carbon emission flow distribution, and calculating the initial value of carbon emission reduction contribution based on the difference in total load carbon flow rate, includes: The first load carbon flow rate of each node is obtained based on the first carbon emission flow distribution, and the pre-response load carbon flow rate is obtained by summing the first load carbon flow rates of all nodes. The second load carbon flow rate of each node is obtained based on the second carbon emission flow distribution, and the load carbon flow rate after response is obtained by summing the second load carbon flow rates of all nodes. Calculate the load carbon flow rate difference between the pre-response load carbon flow rate and the post-response load carbon flow rate; The initial value of the carbon emission reduction contribution is calculated based on the response time of the virtual power plant and the difference in load carbon flow rate.

6. The method for allocating carbon emission reduction contributions from a virtual power plant as described in claim 5, characterized in that, The response time, response deviation, and carbon potential sensitivity of the statistical virtual power plant are used to calculate correction coefficients. These correction coefficients are then used to adjust the initial value of the carbon emission reduction contribution to obtain the effective carbon emission reduction contribution, including: The response time of the virtual power plant is statistically analyzed, and a response time correction parameter is calculated based on the response time. Obtain the dispatch command power curve and the actual response power curve of the virtual power plant, calculate the response deviation based on the dispatch command power curve and the actual response power curve, and calculate the response reliability correction coefficient based on the response deviation; The nodal carbon potential change at the grid connection point of the virtual power plant is statistically analyzed. Based on the nodal carbon potential change and the total response power, the carbon potential sensitivity is calculated. Based on the ratio of the carbon potential sensitivity to the maximum carbon potential sensitivity in the preset area, the carbon potential sensitivity correction coefficient is calculated. The initial value of the carbon emission reduction contribution is corrected based on the response time correction coefficient, response reliability correction coefficient, and carbon potential sensitivity correction coefficient to obtain the effective carbon emission reduction contribution.

7. The method for allocating carbon emission reduction contributions from a virtual power plant as described in claim 6, characterized in that, The process of correcting the initial value of the carbon emission reduction contribution based on the response time correction coefficient, response reliability correction coefficient, and carbon potential sensitivity correction coefficient to obtain the effective carbon emission reduction contribution includes: The response time correction coefficient, response reliability correction coefficient, and carbon potential sensitivity correction coefficient are weighted and summed based on preset weights to obtain a comprehensive correction coefficient. The effective carbon emission reduction contribution is determined by multiplying the initial value of the carbon emission reduction contribution with the comprehensive correction coefficient.

8. The method for allocating carbon emission reduction contributions from a virtual power plant as described in claim 6, characterized in that, The response time includes the response instruction issuance time, the actual response start time, the scheduled response duration, and the actual continuous response duration. The process of statistically analyzing the response time of the virtual power plant and calculating response time correction parameters based on the response time includes: Calculate the time difference between the time the response instruction is issued and the actual response start time. Based on the time difference and the proportion of the scheduling requirement response time, calculate the response speed correction value. Calculate the response duration correction value based on the ratio of the actual continuous response duration to the scheduled response duration. The response time correction parameter is obtained by weighted summing of the response speed correction value and the response duration correction value.

9. The method for allocating carbon emission reduction contributions from a virtual power plant as described in claim 7, characterized in that, The effective carbon reduction contribution is allocated to each distributed resource based on the adjustment amount of each distributed resource, the carbon potential of the first node of the node, and the response quality of each distributed resource, to obtain the carbon reduction contribution corresponding to each distributed resource, including: Based on the resource type, adjustment direction, and adjustment amount of each distributed resource, determine the effective emission reduction adjustment amount of each distributed resource; Based on the effective emission reduction adjustment amount of each distributed resource, the carbon potential of the first node of the node where it is located, and the response time, the basic contribution value of each distributed resource is calculated, and the basic contribution values ​​of all distributed resources are summed to obtain the total basic contribution value. Based on the individual response time, individual execution deviation, and node carbon potential level of each distributed resource, the basic contribution value and the total basic contribution value of each distributed resource are corrected to obtain the corrected contribution value and the total corrected contribution value of each distributed resource. The allocation weight of each distributed resource is determined based on the ratio between the correction contribution value of each distributed resource and the total correction contribution value of the distributed resources. The effective carbon emission reduction contribution is allocated based on the allocation weight to obtain the carbon emission reduction contribution corresponding to each distributed resource.

10. A virtual power plant carbon emission reduction contribution allocation device, characterized in that, include: The module includes a first carbon emission flow distribution calculation module, a second carbon emission flow distribution calculation module, a carbon emission reduction contribution initial value calculation module, a correction module, and an allocation module. The first carbon emission flow distribution calculation module is used to acquire the first operating data before the virtual power plant responds, and calculate the first node carbon potential and the first load carbon flow rate of each node based on the first operating data to generate the first carbon emission flow distribution; The second carbon emission flow distribution calculation module is used to obtain the second operating data after the virtual power plant responds, and calculate the second carbon emission flow distribution based on the second operating data; The carbon emission reduction contribution initial value calculation module is used to calculate the difference in total load carbon flow rate based on the first carbon emission flow distribution and the second carbon emission flow distribution, and to calculate the initial value of carbon emission reduction contribution based on the difference in total load carbon flow rate. The correction module is used to statistically analyze the response time, response deviation, and carbon potential sensitivity of the virtual power plant, calculate the correction coefficient based on the response time, response deviation, and carbon potential sensitivity, and correct the initial value of the carbon emission reduction contribution based on the correction coefficient to obtain the effective carbon emission reduction contribution. The allocation module is used to allocate the effective carbon emission reduction contribution to each distributed resource based on the adjustment amount of each distributed resource, the carbon potential of the first node of the node where it is located, and the response quality of each distributed resource, so as to obtain the carbon emission reduction contribution corresponding to each distributed resource.

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